I lead the ML team at Onfido. We use computer vision and deep learning for online identity verification. From 2015 to 2021, I led the machine learning team for recommendation at Criteo. From 2010 to 2014, I led the computer vision team at Thales Optronics in France.

I graduated with a PhD at MIT in 2010 under the supervision of Prof. Seth Teller. I was a core member the MIT team at the DARPA Urban Challenge in 2007. My work was published at CVPR, ICCV, ICRA and IJFR. I teach the deep learning class at ENSAE Paris.

Posts

• Sept 2024, The Handbook of Applied AI teams
• Jan 2023, AI has crossed the Rubicon. Now what?
• Dec 2022, Building a recommendation engine from scratch
• Sept 2022, Building without Bias at Onfido
• Aug 2022, Where self-driving is headed
• Jan 2022, Lightweight Representation Learning For Efficient And Scalable Recommendation
• Dec 2021, The high road of performance review
• May 2020, The tradeoffs of large-scale machine learning: the price of time
• Feb 2020, Your first 90 days as a tech lead
• June 2019, Making your company machine learning-centric

also on Medium

Featured talks

• 2024, Oct 17th: Fraud Prevention with Computer Vision in the GenAI age, AIAI Boston, slides
• 2023, June 4th: ML Prague, Bringing automation and fairness to identity verification on the internet with deep learning - slides
• 2023, June 21st: An introduction to ChatGPT and generative AI, Point Nine CTO Meetup, Paris - slides
• 2023, March 30th: ChatGPT: have we crossed the Rubicon? Invited talk at BPCE DigiPay Tech+ Event
• 2022, IFTTD podcast: Large-scale AI (in french), youtube video
• 2020, Job interview talk at Onfido, Scalable representation learning and retrieval for online advertising
• 2018, 7th RecSys London Meetup, Acquisition: Recommending Products From a Retailer That the User Never Visited Before
• 2017, Criteo RecSys London, Product recommendation beyond collaborative filtering, welcome to the twilight zone!
• 2016, ICML: Online Advertising Systems Workshop, New challenges for scalable machine learning in online advertising
• Oct 2014, ICIP, Image and Video Processing for Defense, Transportation, Homeland Security, and Observation from Space: Industrial Expectations and Technological Challenges

Publications

• Lightweight representation learning for efficient and scalable recommendation, arxiv:2101.00870v2, Nov 2021
• Ground robot navigation using uncalibrated cameras, ICRA 2010
• PhD Thesis, 2010
• Body-relative navigation guidance using uncalibrated cameras, ICCV 2009 - slides - pdf
• A perception-driven autonomous urban vehicle, IJFR 2008 - pdf
• Wide-area egomotion estimation from known 3d structure, CVPR 2007 - pdf
• SLYK: A Transparent Fault-Tolerant Migration Platform, MIT Technical Report, 2005
• The City Scanning Project: Validation and Algorithms, MIT Technical Report, 2002

also on Google scholar

Teaching

• Teaching the Deep Learning class at Master Level (3rd-year) at ENSAE, since Spring 2024
• Teacher at M2 level at Paris Dauphine University with Criteo, IASD, 2019-2020
• Teacher at the Workshop on Recommendation, Ecole Polytechnique Data Science Summer School, June 2018 & 2019
• Back in 2008, I taught Java at MIT over IAP. This was one of the first courses to end up on opencourseware the following years!

Misc

• Book recommendations for tech leaders.
• I co-founded Reveal, the RecSys workshop for causal recommendation with Microsoft, Netflix and Cornell University. The workshop ran from 2018 to 2020 and now continues as the Consequences workshop.
• In 2015, I won the Criteo 2015 Hackathon (16 teams) with image-based similarity using deep networks: developed an end-to-end pipeline with Python/caffe/cuDNN/protobuf on AWS processing 400K images per hour and shipped to AB test
• Google Hashcode: 5/65 in 2015 Finale Round, 76/1054 in 2016, 300/2815 in 2017
• Finishing Advent of Code 2023 - blog post - github